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Senior Data Scientist, RC Capital
RevenueCatAmericasPosted 5 May 2026
Job Description
Senior Data Scientist, RC Capital
RevenueCat removes the headaches of building and scaling in‑app subscriptions. Since graduating from YC’s S18 batch we’ve grown into the default monetization platform for mobile: we’re in >40% of newly shipped subscription apps, we process $10B+ in annual purchase volume, and we help everyone from a solo dev in Brazil to the OpenAI mobile team understand and grow their revenue.
We’re a remote‑first crew of 120+, spread across 25 countries, and guided by values we actually practice: Customer Obsession, Always Be Shipping, Own It, and Balance. If you want your work to touch hundreds of millions of end‑users (and help the developers behind them get paid), you’ll fit right in.
THE ROLE
We're looking for a Data Scientist to support product initiatives for RevenueCat Capital, with deep experience in lead qualification, anomaly detection, fraud prevention, and underwriting.
This is a chance to be the founding Data Scientist embedded within the Capital team, a greenfield opportunity to scale our new fintech business lines from <$1M to $100M+.
You'll partner directly with leadership, collaborate across teams, and bring a new product to life inside RevenueCat. Your work will touch real money, real developers, and a product that is just getting started. Read more about the opportunity here https://www.notion.so/RC-Capital-the-opportunity-33ccb1a108b080ea9fdef24dfa0caa06?pvs=21.
THE OPPORTUNITY: RC CAPITAL
RevenueCat is on a mission to help developers make more money. We build software that helps apps implement and manage purchases, with over 50% of new subscription apps on the App Store launching with RevenueCat. OpenAI's mobile subscriptions run on RC. Top of funnel metrics are up 300%+ YoY.
RC Capital is our next chapter: we'll continue to help developers make more money, not just through software, but through financial products. Financial institutions would love to have what we already have:
- Trust + distribution: App developers already trust us in their purchase flow — the highest stakes moment in any user journey.
- Real-time, verifiable data: Cross-platform revenue plus leading indicators like installs, trials, conversions, and refunds.
- Unmatched industry insights: We know how apps earn money at scale, which improves underwriting and product design.
Our first product is Daily Payouts https://www.revenuecat.com/daily-payouts: a factoring product that lets developers get app store proceeds sooner. Scaling it is a big challenge, but it’s just the beginning. There’s so much more to build: credit cards, revenue-based lending, cohort-based financing. We’ve got a mountain to climb.
WHAT YOU'LL DO
- Own the Data Science strategy for RC Capital. Build the foundation for our underwriting and fraud detection systems from the ground up. Nothing is locked in, you'll define the models, the signals, and the approach.
- Develop sophisticated models for lead qualification, anomaly detection, fraud prevention, and credit underwriting. All this using the richest, most real-time app revenue data in the world.
- Partner closely with Product and Engineering to integrate risk signals and underwriting logic into customer-facing flows and internal decisioning engines.
- Analyze cross-platform revenue data to uncover insights that improve our underwriting models and product design.
- Build mechanisms for measuring impact, evaluating model performance, and driving prioritization of new data initiatives.
- Operate with high ownership in an ambiguous, fast-moving environment helping to define the long-term vision for our financial products.
ABOUT YOU
You are a Senior Data Scientist who cares deeply about impact and has direct experience with the kind of models that carry real financial consequence. From a skills perspective, you bring:
- You have 5+ years of data science experience, ideally with a strong background in fintech, credit, lending, or payments.
- You have deep expertise in fraud and/or un ... (truncated, view full listing at source)
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